When a user needs help with a topic, such as a software application, the user typically submits a query to a search engine that summarizes the topic. For example, a user having problems with a formatting issue in a word processing application named “Foo” may submit the query “How to do I turn on paragraph numbering in Foo?”
In response, the user may receive search results from the search engine that include links to a variety of webpages from a variety of sources that are responsive to the query. Continuing the example above, the search results may include links to publications about the Foo word processing application that are authored or hosted by the entity that created the application, links to publications by experts or other entities that are not affiliated with the entity that created the word processing application, as well as links to threads on forums or other webpages where users discuss the word processing application and problems and solutions regarding the word processing application.
There are several drawbacks in users finding answers in this way. For example, in order to find an answer, the user may have to visit each of the webpages identified in the search results and read through possibly lengthy publications or discussion threads. Additionally, the user may find conflicting solutions to his question and may lack sufficient information to resolve the conflict. Further, because of a disconnect between how the user chooses to characterize the topic, versus the more technical characterization of the topic that may be used in publications or by experts, the answers that are returned in the search results may not be well tailored to the question provided by the user. Moreover, if the user is unable to find an answer in response to the query, the user may call or directly contact technical support to the resolve the issue, which may be costly to the entity associated with the topic.